MILK: a Python scripting interface to MAUD for automation of Rietveld analysis.

Modern diffraction experiments (e.g. in situ parametric studies) present scientists with many diffraction patterns to analyze. Interactive analyses via graphical user interfaces tend to slow down obtaining quantitative results such as lattice parameters and phase fractions. Furthermore, Rietveld refinement strategies (i.e. the parameter turn-on-off sequences) tend to be instrument specific or even specific to a given dataset, such that selection of strategies can become a bottleneck for efficient data analysis. Managing multi-histogram datasets such as from multi-bank neutron diffractometers or caked 2D synchrotron data presents additional challenges due to the large number of histogram-specific parameters. To overcome these challenges in the Rietveld software Material Analysis Using Diffraction (MAUD), the MAUD Interface Language Kit (MILK) is developed along with an updated text batch interface for MAUD. The open-source software MILK is computer-platform independent and is packaged as a Python library that interfaces with MAUD. Using MILK, model selection (e.g. various texture or peak-broadening models), Rietveld parameter manipulation and distributed parallel batch computing can be performed through a high-level Python interface. A high-level interface enables analysis workflows to be easily programmed, shared and applied to large datasets, and external tools to be integrated with MAUD. Through modification to the MAUD batch interface, plot and data exports have been improved. The resulting hierarchical folders from Rietveld refinements with MILK are compatible with Cinema: Debye-Scherrer, a tool for visualizing and inspecting the results of multi-parameter analyses of large quantities of diffraction data. In this manuscript, the combined Python scripting and visualization capability of MILK is demonstrated with a quantitative texture and phase analysis of data collected at the HIPPO neutron diffractometer.

Deformation-Induced Surface Roughening of an Aluminum-Magnesium Alloy: Experimental Characterization and Crystal Plasticity Modeling.

The deformation-induced surface roughening of an Al-Mg alloy is analyzed using a combination of experiments and modeling. A mesoscale oligocrystal of AA5052-O, obtained by recrystallization annealing and subsequent thickness reduction by machining, that contains approx. 40 grains is subjected to uniaxial tension. The specimen contains one layer of grains through the thickness. A laser confocal microscope is used to measure the surface topography of the deformed specimen. A finite element model with realistic (non-columnar) shapes of the grains based on a pair of Electron Back-Scatter Diffraction (EBSD) scans of a given specimen is constructed using a custom-developed shape interpolation procedure. A Crystal Plasticity Finite Element (CPFE) framework is then applied to the voxel model of the tension test of the oligocrystal. The unknown material parameters are determined inversely using an efficient, custom-built optimizer. Predictions of the deformed shape of the specimen, surface topography, evolution of the average roughness with straining and texture evolution are compared to experiments. The model reproduces the averaged features of the problem, while missing some local details. As an additional verification of the CPFE model, the statistics of surface roughening are analyzed by simulating uniaxial tension of an AA5052-O polycrystal and comparing it to experiments. The averaged predictions are found to be in good agreement with the experimentally observed trends. Finally, using the same polycrystalline specimen, texture-morphology relations are discovered, using a symbolic Monte Carlo approach. Simple relations between the Schmid factor and roughness can be inferred purely from the experiments. Novelties of this work include: realistic 3D shapes of the grains; efficient and accurate identification of material parameters instead of manual tuning; a fully analytical Jacobian for the crystal plasticity model with quadratic convergence; novel texture-morphology relations for polycrystal.

Influence of deformation banding instabilities on small scale yielding of a Mg-Nd alloy revealed by in-situ digital image correlation.

Propagating deformation bands are observed to accommodate the initial plasticity in an as-extruded Mg-1.5Nd alloy under tension using digital-image-correlation. The propagating bands cause an uncommon plateau in the stress-strain response of the alloy prior to restoring a common decreasing work hardening with further straining. Effects of the deformation banding and underlying plateau in the flow stress on small scale yielding are investigated during low cycle fatigue (LCF) and tension of notched specimens. Alternating formation/disappearance of deformation bands in the gauge section of as-extruded LCF specimens during testing is observed to reduce life compared to annealed specimens exhibiting no instabilities. In contrast, the bands deflect the plastic zone ahead of the notch from the principal plane orthogonal to the applied loading inducing positive effect on toughness of the alloy.

White Laue and powder diffraction studies to reveal mechanisms of HCP-to-BCC phase transformation in single crystals of Mg under high pressure.

Mechanisms of hexagonal close-packed (HCP) to body-centered cubic (BCC) phase transformation in Mg single crystals are observed using a combination of polychromatic beam Laue diffraction and monochromatic beam powder diffraction techniques under quasi-hydrostatic pressures of up to 58 ± 2 GPa at ambient temperature. Although experiments were performed with both He and Ne pressure media, crystals inevitably undergo plastic deformation upon loading to 40-44 GPa. The plasticity is accommodated by dislocation glide causing local misorientations of up to 1°-2°. The selected crystals are tracked by mapping Laue diffraction spots up to the onset of the HCP to BCC transformation, which is determined to be at a pressure of 56.6 ± 2 GPa. Intensity of the Laue reflections from HCP crystals rapidly decrease but no reflections from crystalline BCC phase are observed with a further increase of pressure. Nevertheless, the powder diffraction shows the formation of 110 BCC peak at 56.6 GPa. The peak intensity increases at 59.7 GPa. Upon the full transformation, a powder-like BCC aggregate is formed revealing the destructive nature of the HCP to BCC transformation in single crystals of Mg.

Rare-earth- and aluminum-free, high strength dilute magnesium alloy for Biomedical Applications.

Lightweight, recyclable, and plentiful Mg alloys are receiving increased attention due to an exceptional combination of strength and ductility not possible from pure Mg. Yet, due to their alloying elements, such as rare-earths or aluminum, they are either not economical or biocompatible. Here we present a new rare-earth and aluminum-free magnesium-based alloy, with trace amounts of Zn, Ca, and Mn (≈ 2% by wt.). We show that the dilute alloy exhibits outstanding high strength and high ductility compared to other dilute Mg alloys. By direct comparison with annealed material of the same chemistry and using transmission electron microscopy (TEM), high-resolution TEM (HR-TEM) and atom probe tomography analyses, we show that the high strength can be attributed to a number of very fine, Zn/Ca-containing nanoscale precipitates, along with ultra-fine grains. These findings show that forming a hierarchy of nanometer precipitates from just miniscule amounts of solute can invoke simultaneous high strength and ductility, producing an affordable, biocompatible Mg alloy.

Residual Ductility and Microstructural Evolution in Continuous-Bending-under-Tension of AA-6022-T4.

A ubiquitous experiment to characterize the formability of sheet metal is the simple tension test. Past research has shown that if the material is repeatedly bent and unbent during this test (i.e., Continuous-Bending-under-Tension, CBT), the percent elongation at failure can significantly increase. In this paper, this phenomenon is evaluated in detail for AA-6022-T4 sheets using a custom-built CBT device. In particular, the residual ductility of specimens that are subjected to CBT processing is investigated. This is achieved by subjecting a specimen to CBT processing and then creating subsize tensile test and microstructural samples from the specimens after varying numbers of CBT cycles. Interestingly, the engineering stress initially increases after CBT processing to a certain number of cycles, but then decreases with less elongation achieved for increasing numbers of CBT cycles. Additionally, a detailed microstructure and texture characterization are performed using standard scanning electron microscopy and electron backscattered diffraction imaging. The results show that the material under CBT preserves high integrity to large plastic strains due to a uniform distribution of damage formation and evolution in the material. The ability to delay ductile fracture during the CBT process to large plastic strains, results in formation of a strong <111> fiber texture throughout the material.

Using association rule mining to identify risk factors for early childhood caries.

BACKGROUND AND OBJECTIVE: Early childhood caries (ECC) is a potentially severe disease affecting children all over the world. The available findings are mostly based on a logistic regression model, but data mining, in particular association rule mining, could be used to extract more information from the same data set. METHODS: ECC data was collected in a cross-sectional analytical study of the 10% sample of preschool children in the South Backa area (Vojvodina, Serbia). Association rules were extracted from the data by association rule mining. Risk factors were extracted from the highly ranked association rules. RESULTS: Discovered dominant risk factors include male gender, frequent breastfeeding (with other risk factors), high birth order, language, and low body weight at birth. Low health awareness of parents was significantly associated to ECC only in male children. CONCLUSIONS: The discovered risk factors are mostly confirmed by the literature, which corroborates the value of the methods.

Delineation of First-Order Elastic Property Closures for Hexagonal Metals Using Fast Fourier Transforms.

Property closures are envelopes representing the complete set of theoretically feasible macroscopic property combinations for a given material system. In this paper, we present a computational procedure based on fast Fourier transforms (FFTs) to delineation of elastic property closures for hexagonal close packed (HCP) metals. The procedure consists of building a database of non-zero Fourier transforms for each component of the elastic stiffness tensor, calculating the Fourier transforms of orientation distribution functions (ODFs), and calculating the ODF-to-elastic property bounds in the Fourier space. In earlier studies, HCP closures were computed using the generalized spherical harmonics (GSH) representation and an assumption of orthotropic sample symmetry; here, the FFT approach allowed us to successfully calculate the closures for a range of HCP metals without invoking any sample symmetry assumption. The methodology presented here facilitates for the first time computation of property closures involving normal-shear coupling stiffness coefficients. We found that the representation of these property linkages using FFTs need more terms compared to GSH representations. However, the use of FFT representations reduces the computational time involved in producing the property closures due to the use of fast FFT algorithms. Moreover, FFT algorithms are readily available as opposed to GSH codes.